How AI is rewriting consumer commerce in China

As demand growth falters and traditional stimulus offers only limited lift, China’s biggest consumer platforms are leaning into AI not as a moonshot, but as a practical tool to stabilize margins, reshape competition, and extract more value from each transaction.

Unlike in Western markets—where AI in retail has largely stayed behind the scenes in analytics and operations—Chinese platforms are increasingly putting AI directly in front of consumers. Search, discovery, pricing, and even the language used to sell products are being algorithmically optimized in real time. The result is a subtle but significant rewrite of how consumer commerce works in the world’s largest online retail market.

For investors, this shift helps explain a seeming paradox: why some Chinese consumer-tech firms are managing to protect profitability despite weak headline spending data.

China’s e-commerce ecosystem has long been data-rich, but AI is now reshaping how it’s used in consumer interactions. Platforms are embedding AI-driven search, chat, and recommendation tools directly into core shopping experiences, guiding users through huge product catalogs with far less friction than traditional browsing.

Beijing shopper Li Wei, 29, describes the change in practical terms: “When I’m not sure what brand to choose, I just ask the AI—it shows me options tailored to my needs and helps me compare quickly. It’s like having a friend who knows every store," she says.

Major platforms such as Alibaba Group and JD.com have emphasized these AI upgrades in earnings communications, framing them less as experimental features and more as tools to improve conversion rates and user engagement.

During Alibaba’s most recent quarterly update, CFRA analyst Angelo Zino said, “We believe these investments (in consumption and AI) will build long-term competitive advantages despite near-term margin pressures."

In this environment, control over the AI layer increasingly means control over demand.

As AI reshapes how consumers discover products, competition among platforms is shifting away from scale alone toward algorithmic effectiveness. The traditional home page—once a static grid of promotions—is becoming a personalized, constantly updating interface shaped by real-time signals.

Platforms with richer data sets spanning shopping, payments, logistics, and offline behavior are better positioned to push higher-margin goods, optimize promotional timing, and reduce marketing waste. For brands, visibility increasingly depends on how products perform within opaque recommendation systems rather than on advertising spend alone.

This shift also strengthens platform leverage over merchants as regulators are paying closer attention to algorithmic transparency and fairness. The competitive advantage from AI is real, but so are the constraints shaping how far platforms can push it.

In a slowing consumer economy, AI’s most immediate value lies not in top-line growth but in efficiency. Platforms are using AI to forecast demand more accurately, optimize inventory placement, shorten delivery times, and manage costs across sprawling logistics networks.

Dynamic pricing models—long controversial in China—are becoming more sophisticated, adjusting not only for demand but also for timing, user behavior, and competitive context. AI is also automating customer service, streamlining returns, and reducing fraud, all of which feed directly into operating margins.

That focus helps explain why some consumer platforms have reported margin resilience even as revenue growth moderates. Alibaba CEO Eddie Wu has brushed off concerns about an AI investment bubble, telling investors the company will invest “aggressively" in AI infrastructure because demand reflects real adoption rather than hype.

Offline retail plays a quieter but important role in this transformation. China’s push toward “smart retail"—integrating in-store behavior with online data—provides platforms with valuable training material for AI models.

Sensors, loyalty programs, and digital payment systems allow companies to track how online browsing translates into physical purchases and vice versa. That feedback loop improves recommendation accuracy and demand forecasting, reinforcing the advantage of platforms with both online and offline reach.

For investors, this helps explain why companies with integrated ecosystems may retain an edge over narrower e-commerce players, even in a tougher consumer environment.

AI’s growing role in consumer commerce isn’t without risk. Regulators have repeatedly warned against opaque algorithms and discriminatory pricing, and consumer trust remains fragile. There is also the risk of diminishing returns: as more platforms deploy similar tools, AI may become a baseline cost of doing business rather than a lasting differentiator.

Execution matters, and missteps—whether regulatory, technical, or reputational—could quickly erode the gains AI delivers.

China’s consumer story is no longer just about confidence or income growth. It is increasingly about infrastructure—specifically, the invisible systems shaping how consumption happens.

AI is becoming that infrastructure. For investors, understanding how platforms deploy it helps clarify why certain Chinese consumer-tech stocks continue to show resilience, how competition is evolving beneath the surface, and where regulatory and execution risks may emerge next.

In a slower-growth China, the winners may be less those who sell more than those who sell smarter.

Write to editors@barrons.com